Quantitative Researcher (Mulitple Openings)
Research and deploy trading algorithms by analyzing market data, developing statistical signals and tools, and improving simulations to support high- to mid-frequency trading and live execution.
Aptura is an applied AI and data company working with frontier labs to train AI systems on real professional work. We do this by building high-quality evaluation and training environments that teach AI agents to produce work that can be used in daily workflows.
We are looking for Subject Matter Experts with experience in legal roles who have spent real time building board legal updates, transaction packs, and compliance decks.
Responsibilities include:
Designing "problems" to test state-of-the-art AI models on your workflows (ex. designing tasks that start mid-workflow - this can be a board legal update that's work in progress, a closing pack that needs revised deal terms or a compliance training deck moving into a new template)
Working with frontier engineering/research teams to implement and evaluate AI systems on the designed real-world legal work.
Necessary Skills include:
3+ years in an in-house legal, company secretarial, or compliance role with deep hands-on PowerPoint work
Ability to define what "good" looks like precisely enough for someone else to grade against it
Attention to detail, and willingness to learn concepts in AI and data
Remote or In-office (Liverpool Street, London)
Hourly: $100/hour
Research and deploy trading algorithms by analyzing market data, developing statistical signals and tools, and improving simulations to support high- to mid-frequency trading and live execution.
Collect and interpret environmental samples and data, support due diligence and Massachusetts Contingency Plan reporting, and contribute to fieldwork and project documentation alongside environmental staff and managers.
Develop and optimize analytical methods, execute biochemical testing, troubleshoot assays and instruments, and communicate data-driven findings while supporting compliant laboratory operations and cross-functional project delivery.
Design and deliver real-world healthcare studies, analyse large datasets, and communicate findings to clients and external stakeholders, contributing evidence for publications, health economic models, and health technology assessment.
Post-train open-source LLMs for specialized customer tasks by turning domain-specific data into reward functions, agent environments, evaluations, and training pipelines that improve production models.